[1]马靖,严洪森,杨钦贺. 海洋环境武器效能的改进RBF网络评估模型[J].计算机技术与发展,2015,25(01):19-23.
　MA Jing,YAN Hong-sen,YANG Qin-he. Improved RBF Network Evaluation Model of Weapon Operational Effectiveness under Marine Environment[J].,2015,25(01):19-23.
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 海洋环境武器效能的改进RBF网络评估模型()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
25
期数:
2015年01期
页码:
19-23
栏目:
智能、算法、系统工程
出版日期:
2015-01-10

文章信息/Info

Title:
 Improved RBF Network Evaluation Model of Weapon Operational Effectiveness under Marine Environment
文章编号:
1673-629X（2015)01-0019-05
作者:
 马靖; 严洪森; 杨钦贺
 东南大学 复杂工程系统测量与控制教育部重点实验室；东南大学 自动化学院
Author(s):
 MA Jing; YAN Hong-sen; YANG Qin-he
关键词:
 ; 作战效能; 评估模型; RBF神经网络; 海洋环境; 武器装备
Keywords:
 ; operational effectiveness; evaluation model; RBF neural network; marine environment; weapon equipment
分类号:
TP31
文献标志码:
A
摘要:
 文中针对海洋环境影响下单武器装备作战效能的评估问题，建立基于RBF神经网络的评估模型。在实际应用中，为了保证评估结果的客观性和准确性，提出一种基于统计原理的改进RBF神经网络模型。该改进模型采用基于样本相似度的聚类算法，以加权欧氏距离为样本相似性度量方法，通过对样本进行聚类处理得到RBF神经网络模型的参数，进而建立评估模型。最后，为了验证提出模型的可行性，利用样本实例对模型进行训练，并利用训练后的模型对某一环境下单一武器作战效能进行评估，实验结果表明了模型的可行性和可靠性。和传统方法相比，该评估模型基于样本数据的统计信息，不需要专家知识，具有较高的客观性。
Abstract:
 An evaluation model based on RBF neural network is established to solve the evaluation problem of single weapon equipment operational effectiveness under the influence of marine environment. In practical application,to ensure that the evaluation result is objec-tive and exact,an improved RBF evaluation model based on principle of statistics is proposed here. The improved model uses clustering algorithm based on the sample similarity and utilizes weighted Euclidean distance as measure method of sample similarity,to get the pa-rameters of RBF neural network model by clustering process on sample data and then establish the model. Finally,to verify the feasibility of the proposed model,a set of actual sample data is used to train the model and use the trained model to evaluate the operational effec-tiveness of single weapon equipment under the influence of marine environment. The test has showed the feasibility and reliability of pro-posed model. Compared with the traditional methods,the evaluation model proposed is based on the statistics of sample data and needs no expertise,which makes the evaluation results more objective.

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更新日期/Last Update: 2015-04-17